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Fernández, N., S. Kramer-Schadt, and H. Thulke. 2006. Viability and risk assessment in species restoration: planning reintroductions for the wild boar, a potential disease reservoir. Ecology and Society11(1): 6. [online] URL: http://www.ecologyandsociety.org/vol11/iss1/art6/Research

Viability and Risk Assessment in Species Restoration: Planning Reintroductions for the Wild Boar, a Potential Disease Reservoir

The reintroduction of large mammals is often considered a priority conservation action in highly industrialized countries in which many of these species have been depleted. However, species reintroduction after decades of absence may involve important risks for human activities and ecological communities, such as favoring the spread of diseases. An example of a potentially troublesome reintroduction is the wild boar, which may act as a reservoir of diseases, e.g., classical swine fever, and cause high economic losses, and has become a species of concern in several European countries for both ecological and recreational reasons. Failure to prevent the disease consequences of species restoration can negate its conservation benefits. Here we evaluated the probability of both successfully reintroducing wild boar into Denmark and limiting their contact with domestic pig farms to which they might spread disease. For this purpose, we developed a spatially explicit, individual-based population model that incorporates information on boar habitat and demography information from Central European populations. We then compared model predictions with the spatial distribution of farms to achieve a spatial assessment of the contact risk. The most restrictive model scenario predicted that nearly 6% of Denmark provides habitat conditions that would allow wild boar to reproduce. The best habitats for reintroduction were aggregated in seven different areas throughout the country in which the extinction probability was < 5%. However, the expected population expansion was very limited in most of these areas. Both the number of suitable areas and the potential for population expansion greatly increased when we relaxed our habitat assumptions about boar forest requirements; this provided a more conservative scenario for a cautious risk analysis. We additionally found that part of the risk of contact with piggeries was associated with the magnitude of the expansion, although the nonrandom spatial pattern of farm distribution also had a strong influence. The partitioning of risks into those related to population expansion and those related to farm distribution allowed us to identify trade-offs between restoring boar populations and minimizing risks in different potential areas and under different risk scenarios; as a result, we rejected some of the particularly high-risk areas for potential reintroduction of the species. Our approach illustrates how the joint quantification of anticipated reintroduction success and associated risks can guide efforts aimed at reconciling species recovery and the affected health and economic interests.

Species reintroduction is a key tool for the conservation of animal
biodiversity. Often it is considered the only remaining option for
ecological restoration in many regions, particularly industrialized
countries, in which the native fauna has been decimated and natural
recolonizations are unlikely to occur. Examples can be found in Central
and Western Europe, where land-use changes and direct persecution have
caused the decline and local extinction of numerous vertebrate
populations in recent centuries (EEA 2003). Because of their concerns
about environmental degradation, present-day societies in these
countries are demanding that this “lost nature” be recovered, and
national and international conservation policies are increasingly
regarding the issue of species reintroduction as an added value for
both ecosystem and social welfare (IUCN 1998). However, reintroduction
after decades of absence may also have a negative impact on ecosystems
and on human activities comparable to the introduction, deliberate or
not, of alien species. Indeed, reintroductions may conflict with
different conservation and economic interests, e.g., if the new
population competes with other species or alters their habitats, causes
damages to crops, or acts as a disease reservoir (Mack et al. 2000).
Therefore, reintroduction planning must be based on a careful
identification of the specific negative consequences that it may carry
and on estimates of how likely they are to occur (Simberloff et al.
2005).

Among vertebrates, large mammals are often chosen for restoration
projects because they face a high extinction risk, because they play
key roles in ecological communities, or just because they're “sexy”
(Maehr et al. 2001). Consequently, this preference for large mammals is
not necessarily a response to global threats but may also reflect
aesthetic or recreational values; as a result, programs aiming to
restore regional biodiversity often include many widely distributed
species with no imminent risk of extinction (Seddon et al. 2005). For
example, although the wild boar (Sus scrofa) is a common species
in many areas of Europe, Asia, and North Africa and has been introduced
into other regions, it is nevertheless a species of conservation
concern in several European countries in which it has been depleted. In
the last four centuries, wild boars have disappeared or become relict
in, e.g., the UK, the Scandinavian countries, and Denmark, as a result
of habitat loss caused mostly by deforestation and overhunting. Wild
boar recovery has been proposed or already started from captive
populations in some of these countries (Howells and Edwards-Jones 1997,
Lemel et al. 2003, Alban et al. 2005).

However, reintroducing the wild boar may conflict with different
conservation and economic interests, because its populations can alter
the community structure and biodiversity of local plants through ground
rooting and browsing (Hone 2002, Kuiters and Slim 2002), cause
considerable damage to crop fields (Schley and Roper 2003), and
transmit diseases to livestock that result in high economic losses
(Fritzemeier et al. 2000). Indeed, the wild boar is a potential
reservoir of important diseases such as classical swine fever (CSF), a
viral disease that has caused highly significant economic losses in
Europe (Meuwissen et al. 1999). Boar can infect domestic pigs through
direct contact or through human mediation (Artois 2002, de Vos et al.
2003); for example, up to 60% of CSF outbreaks in domestic pig farms in
Germany have been attributed to the cycling of the disease in wild boar
populations (Fritzemeier et al. 2000). In turn, wild boar contagion
from domestic pigs may also help to propagate the disease and make
control more difficult in both wild boar populations and on farms
(Artois 2002). Therefore, the role of wild boars as a disease reservoir
pits conservation plans against the interests of the farming industry
and reveals the need to assess the risks associated with restoration.
This assessment requires the development of new methods that take into
account both the expected success of the reintroduction and potential
conflicts over the affected areas and can guide proactive prevention
measures in locations at risk.

In the present study, we evaluated planned reintroductions of wild boar
in Denmark together with the associated risk of contact with pig farms.
Although these reintroductions are currently under consideration (Alban
et al. 2005), there are strong concerns about the potential increase in
the CSF risk for the pig-farming industry, one of the most relevant
economic activities in the country and one that produces 62.7% of its
annual exports. In this context, restoration efforts need to be
preceded not only by an assessment of the likelihood of establishing a
free-ranging population but also by measures to prevent the associated
negative consequences (IUCN 1998). We first investigated the viability
of reintroduced populations using habitat and demographic models. For
this we used the available information on wild boar ecology from
Central European populations to determine habitat availability and to
parameterize an individual-based, spatially explicit model simulating
boar demography. This model made possible the explicit consideration of
population dynamics in real landscapes with heterogeneous habitat
distribution and quality. In a second step, we confronted model
simulation results with information on spatial farm distribution to
assess the risk of contact between expanding wild boar populations and
domestic pigs. Our approach can be adapted to the assessment of other
conflicts, such as the alteration of ecosystems, damage to crops, etc.,
that are associated with the introduction of extinct or alien species,
and to the evaluation of population management strategies in relation
to these risks.

Habitat suitability for wild boars was assessed in Denmark based on previous knowledge of the species habitat in Central and Northern Europe. These populations have been shown to be strongly linked to the forests in which they can find primary resources such as food and refuge (Boitani et al. 1994, Groot Bruinderink et al. 1995, Leaper et al. 1999). Forests provide mast, the preferred diet of the wild boars in these regions (Schley and Roper 2003). The species is also reported to take advantage of agricultural landscapes, feeding in crop fields and grasslands mostly in spring and summer (Boitani et al. 1994, Schley and Roper 2003); however, wild boars in these landscapes have been shown to depend on the proximity of woodlands and other sheltering natural vegetation for resting and breeding (Cargnelutti et al. 1990, Gerard et al. 1991). Therefore, wild boar habitat in temperate Europe is mostly characterized by forests and other landscapes in which at least some proportion of woodland can be found. Although there is a lack of studies analyzing minimum vegetation requirements for wild boar, the species can be found in some regions in which only 10% of the landscape is covered by woodland and other sheltering vegetation.

The density of individuals in Central European wild boar populations is
also influenced by the structure of the forests that determine yearly
mast productivity and therefore wild boar reproduction and mortality
rates (Pucek et al. 1975, Andrzejewski and Jezierski 1978, Groot
Bruinderink et al. 1994, Jedrzejewska et al. 1994, Groot Bruinderink et
al. 1995, Jedrzejewska et al. 1997). Jedrzejewska et al. (1994) found
that the percentage of area covered by stands of deciduous trees
explained up to 64% of the variance in wild boar biomass in exploited
forests of Poland. From these data, wild boar density can be related to
forest composition using the following regression (Fig. 1):

y = 0.76 (±0.44) + 0.05(±0.01)%Dec

(1)

where y is the number of wild boars/km² and %Dec
is the percent area covered by deciduous forests. Values in brackets
are standard errors.

Based on this information, we modeled the potential distribution of
wild boar habitat in Denmark using the following steps:

We set the spatial resolution for habitat evaluation at 4
km², the approximate mean size of the home ranges of a variety of
European wild boar populations (Spitz and Janeau 1990). We generated a
grid of Denmark composed of 2 x 2 km cells to simulate the home ranges
of wild boar. The vegetation composition of these cells was identified
by matching the grid to a Land Cover Map of Denmark with a 30-m
resolution produced from the classification of 20 Landsat TM images
spanning the period from 1992 to 1997 (Groom and Stjernholm 2001). We
then estimated the percentage of the cell area covered by (1) conifer
forest, (2) deciduous and mixed forest, (3) other natural vegetation
providing cover, e.g., bush, heathland, etc., and (4) water bodies. The
latter class was used to identify barriers to dispersal.

Cells with 10% of their areas covered by forests and
natural vegetation were assigned to the category of nonbreeding
habitat. However, this minimum amount of forest is probably still not
enough for northern wild boar populations, for whom forest can become
the only source of food in winter. Therefore, we evaluated alternative
scenarios with stricter forest requirements, gradually increasing
minimum forest coverage by 5% up to 50% of the cell area.

Habitat capacity was estimated for each habitat cell based
on the proportion of deciduous and mixed forest identified using Eq. 1.
The intercept of this equation sets wild boar density for habitats with
no deciduous forest. Although wild boars in Central Europe can reach
densities well above this value in regions with a low proportion of
deciduous trees, this is often because of an artificial food supply in
winter, when mast availability plays an important regulatory role in
other populations. Our estimates are therefore conservative so that we
can detect areas in which a viable wild boar population can persist
without an artificial food supply. Habitat capacity was used to
estimate the potential number of breeding females in the cell, assuming
an average ratio of [N breeding females]:[N wild boars] =
1:4.

The potential distribution of wild-boar home ranges and
their quality, i.e., the potential number of breeding females, was
mapped for the different scenarios of forest requirements. The habitat
maps provided the basis for simulations of the individual-based
population model.

We considered farms to be at risk if located within the 3 x 3 cell
neighborhood of a cell in which reproduction occurred during the
simulation period; this was taken to be a signal of herd establishment.
This buffer was adequate to estimate the risk of CSF neighborhood
infections, i.e., not mediated by human transport, which decreases from
the source of the infection down to 500 m in domestic pigs (Staubach et
al. 1997, Crauwels et al. 2003). For every simulated reintroduction,
the contact risk was estimated as the number of farms in these buffers
averaged over the 100 simulations. The risk measure was mapped for all
cells to achieve a spatial risk representation. We expected a
correlation between the mean number of farms at risk and the population
expansion, because more farms would be affected with higher wild-boar
colonization. However, the heterogeneous distribution of farms may also
influence spatial variations in risk. In this case, the residuals of
the relation between risk estimation and population expansion revealed
the effect of spatially nonrandom patterns in farm distribution. To
measure this effect, we compared the risk estimated from the original
simulations with a null model simulating the same population expansion
in landscapes with random farm distribution. A Monte Carlo approach was
performed by randomizing the farm locations on the map before the
population dynamics and remeasuring the number of farms at risk at the
end of the simulation period. The randomization procedure was repeated
100 times per reintroduction to estimate the full distribution of the
number of farms at risk under the assumption of randomly located farms.

Finally, we determined the probability value of the original farm
assemblage in the Monte Carlo distribution and assigned the
corresponding percentile score to the focal cell. These scores were
mapped to visualize the trade-off between reintroduction success and
relative risk to farms in the different reintroduction areas.

Potential wild boar habitat in Denmark represented more than 40% of the
total area under the more relaxed assumption of 10% forest cover
requirements. However, only 22.7% of the country showed the expected
wild boar density of more than one individual per square kilometer
(1/km²), the minimum density found throughout many European
populations (e.g., see revisions by Howells 1997, Leaper 1999). Habitat
prediction was very sensitive to assumptions regarding minimum forest-cover requirements (Fig. 2), to the extent that only 5.7% of the study
area is potential habitat if 50% cover is assumed. Larger requirements
would imply even lower habitat availability and, in that case,
reintroduction programs would probably not succeed. Habitats with
expected wild boar densities of < 1/km² always represent
approximately 50% of the total habitat under all assumptions about
forest coverage (Fig. 2). This indicates that, in general, forests in
Denmark are not likely to sustain high densities of wild boars.

Viability of the
reintroduction

The success in terms of population persistence of simulated wild boar
reintroductions differed greatly among focal release areas (Fig. 3).
Holding to the most restrictive assumption of 50% forest required for
home range acquisition (Fig. 3B), the spatially explicit demographic
model predicted an aggregation of suitable reintroduction cells around
four areas in the Jutland Peninsula and two in Sealand in which wild
boar populations would persist with a probability of > 95%. However,
Central Jutland and North Sealand were the only areas in which
simulations resulted, on average, in population expansions larger than
four times the initial population (Fig. 3D). The number of favorable
reintroduction locations greatly increased as the required forest
assumption was relaxed, with a maximum expansion of 640 km² after
50 yr of simulation under the most optimistic scenario.

Reintroduction success was associated with habitat availability, i.e.,
the number of habitat cells around the place of release, and with
breeding capacity, i.e., the maximum possible number of breeding
females within those cells (Fig. 4). For the most restrictive habitat
scenario of 50% forest, the highest correlations between extinction
rate and habitat variables occurred at scales between a radius of 11
and 17 km. This suggests that reintroduction success will depend on the
availability of high-quality habitats over areas ≥ 380 km². As
seen in Fig. 4B, the correlation with breeding capacity was stronger
(Spearman's correlation: p ≤ -0.60 between scales 11 and 15),
indicating that, beyond habitat availability, quality plays also a
primary role in guaranteeing successful reintroductions. With respect
to population expansion, the highest correlations were observed with
habitat availability at spatial scales between a radius of 17 and 27 km
(p ≥ 0.85), as seen in Fig. 4C.

The outcome of simulated reintroductions under the most optimistic
habitat assumption was only weakly correlated with habitat availability
and quality at any spatial scale (all p < 0.14), indicating
that habitat was not limiting in this scenario.

Farms at risk

The number of farms at risk was moderately correlated with the
population expansion in the scenario with a forest requirement of 10% (p = 0.69, P < 0.001 in all farms and in extensive farms), and only weakly when the forest requirement was 50% (all farms: p = 0.55, P < 0.001; extensive farms: p = 0.29, P < 0.001). Additionally, we found that the
aggregated distribution of farms had a strong effect on the contact
probability with reintroduced wild boars. This is shown by the fact
that the number of affected farms differed greatly from the predictions
of the simulated expansions in the random farm-distribution scenario.

We based our geographical risk analysis on a cautious approach by
investigating the scenario that results in a larger expansion of the
wild boar population, i.e., the 10% forest requirement (Figs. 5A and
5B). In general, the number of extensive farms at risk was low compared
with the total number of farms, with a maximum of 26 extensive farms
contacted by a colonizing wild boar population. In contrast, some
scenarios resulted in more than 300 farms at risk when closed piggeries
were also included. The highest number of farms in contact with wild
boars was associated with releases in the middle of Jutland in the
Silkeborg Forest and in Sealand.

However, population expansion did not completely account for the number
of farms at risk. For example, when we compared the risk in northern
Sealand with the results of the Monte Carlo simulations of the null
model, we found that fewer farms were affected than expected from the
sole effect of population expansion, whereas the opposite was observed
in the northeast of Jutland (Fig. 5C). In some areas the estimated risk
depended on the type of farm considered. With regard only to outdoor
farms, northern Sealand becomes less favorable for reintroduction
because of the disproportionate risk of contact in relation to the wild
boar expansion (Fig. 5D). For the same reason, Fyn Island and a large
area in the west of Jutland are not suitable either.

Figure 6 summarizes the trade-off between population expansion under
the most restrictive habitat scenario and the relative risk to farms
for the areas in which the extinction probability of the reintroduced
populations was low, i.e., < 5%. Cautious reintroduction options are
reduced to three small areas in the north of Jutland in which the
expansion is much smaller but the risk of contact to farms is
relatively low. The risk is proportional to the expansion in Central
Jutland, the most favorable area for achieving the reintroduction
objectives.

Species restoration must be founded on prior assessments of population
viability and associated risks, which are only possible when there is a
clear understanding of the interactions between the demographic traits
of the species and the landscapes designated as targets for
reintroduction. Based on this premise, we developed a spatially
explicit approach to quantify both the reliability of wild boar
reintroductions in Denmark and their risks for the pig-farming
industry. Based on the assumption that appropriate habitats would
contain at least 50% forest, only 22% of the potential release sites
were found to be suitable for achieving a population containing more
than 100 breeding females, whereas most of the simulations reached this
number if the proposed site contained only 10% forest. Given this
variability, wild-boar recovery plans should consider the most
restrictive scenario for the selection of release areas to maximize the
probability of reintroduction success. Using this criterion, we
identified up to seven potential areas with low extinction probability,
i.e., < 5% under the restrictive scenario, distributed in Sealand
and in the centre of Jutland, in which simulated populations expanded
over larger areas. Future landscape changes are not projected in these
results, although they can be relevant for reintroduction success
(Carroll et al. 2003); for example, there are conservation plans for
increasing forest cover in Denmark that will likely favor wild-boar
habitat availability in the future (Alban et al. 2005). However, we
were interested in discovering the most suitable areas for
reintroduction under current conditions so that managers can
incorporate our predictions before forest recovery plans go into effect.

The outcome of reintroductions was strongly associated with both the
availability and the mean quality of the habitats for reproduction
around release sites. In our model, the expansion of reintroduced
populations was a consequence of female dispersal and home range
acquisition in unoccupied habitat cells. Landscapes with a low
proportion of suitable habitat resulted in reduced connectivity, which
made it harder for dispersing individuals to acquire a home range and
led to small populations more vulnerable to extinction, particularly in
the most restrictive habitat scenario. However, habitat quality also
played a major role in population persistence, as shown by the higher
correlation coefficients between extinction rate and potential female
density. High-quality habitats represent an increased capacity for
reproductive individuals, allowing the persistence of larger
populations in reduced areas. This explains the low extinction rates in
most focal reintroduction areas of Sealand as compared with the Jutland
Peninsula, even though population expansion was generally larger in the
latter. These results reveal the need to consider not only habitat
distribution and size but also spatial variations in habitat quality
that may influence the reproductive performance of individuals when
assessing species reintroduction success and population viability in
general (Wiegand et al. 1999).

The conservation purpose of achieving an expanding wild-boar population
clearly conflicts with health and economic concerns related to the
potential transmission of disease between wild boars and domestic pigs,
particularly classical swine fever (Artois et al. 2002, Alban et al.
2005). We observed that the number of farms in contact with an
expanding wild-boar population was only partly correlated with the size
of the expansion. Indeed, the spatial pattern of farm distribution had
also a strong effect. This finding suggests that the restoration of
wild boar in some areas would entail a higher risk compared with the
reintroduction goals. Partitioning the risk contributed by population
expansion and the distribution of exposed farms made it possible to
evaluate the trade-offs between maximizing restoration and minimizing
risk. This distinction is critical for optimizing preventive measures,
like those intended to inhibit contact between domestic and wild pigs.

The distribution of high-risk areas differed depending on whether all
or only outdoor farms were considered, both in absolute terms as well
as in relation to the expected population expansion. One controversial
result is that Northern Sealand, one of the most suitable regions for
reintroducing the species, was a high-risk area for outdoor farms in
relation to the expected expansion (Fig. 6). This risk was not manifest
when all types of farms were included in the evaluation: the total
number of farms potentially in contact with wild boars was noticeably
low both in absolute and relative terms. Results also advise against
reintroductions in Fyn Island because of the high relative density of
outdoor farms. Under this criterion, only some peripheral areas of
Jutland represent a low risk both in absolute and relative terms,
although the strictest habitat scenario also predicts a high
probability of failure in reintroducing the species in most of them.
Central Jutland provides, under all scenarios, the best conditions for
an expanding wild boar population and a proportional risk of contact
with farms. This area is probably the most convenient for the species'
restoration, although the large expected expansion will require
significant preventive efforts to effectively isolate wild boars and
domestic pigs on a high number of outdoor farms.

Evaluating habitat availability and connectivity for reintroduction is
often problematic because of the lack of data on habitat associations
and demography for the areas in which the species went extinct
(Kramer-Schadt et al. 2005). We have shown that the incorporation of
ecological knowledge from other persisting populations can help in
developing predictive habitat and population models to assess the
viability of wild boar reintroduction under these constraints. However,
incomplete knowledge of habitat selection and dispersing behavior may
represent a limitation. For example, we did not consider the effects on
dispersal movement in the matrix (Wiegand et al. 2005) of either
landscape structures or barriers other than water bodies, such as
fences, roads, etc., which could lower the viability of reintroduced
populations and limit their expansion and the associated risks. In this
sense, the detailed monitoring of the population after reintroduction
is essential to evaluate model predictions with regard to both
viability and risk and to update the models as data from the new
population become available (Bar-David et al. 2005). Other parameters
such as mortality may vary greatly among populations depending on
factors such as hunting pressure. Therefore, the monitoring of these
parameters is also crucial and may help to redesign population
management strategies to attain the goals of restoration while
minimizing associated risks.

This study focused on the potential contact between wild boars and
domestic pigs that could involve the risk of disease transmission,
particularly classical swine fever (CSF). The most likely pathways of
CSF infection in wild boar are spread from other populations and
contact with infected domestic pigs, including insufficient
prophylactic measures during pig handling (Fritzemeier et al. 2000).
However, our lack of knowledge about the population-related factors
that affect disease persistence in wild boar limits our ability to
assess risks from reintroductions that may result, for example, in
different population sizes. Larger population size (Artois et al. 2002)
and density (Rossi et al. 2005) may increase CSF persistence in the
wild boar, but the disease has also circulated in small foci and at low
densities of 1–3 individuals/km² (Laddomata et al. 1994, Guberti
et al. 1998). This implies that virtually all viable populations in
Denmark involve some risk of endemic disease in the event of infection,
although the most successful reintroductions involving larger
population sizes and higher densities will likely provide better
conditions for the persistence of the disease.

In summary, the joint quantification of the expected success and risks
represents a promising contribution in species restoration that is only
possible in the framework of spatially explicit models that incorporate
an in-depth understanding of the life-history traits of the species.
The individual-based approach made it possible to model the population
expansion and its associated risks in the absence of previous
demographic data, an inherent drawback in reintroduction studies. We
believe that this approach can help to overcome the “unpredictability
of introduction impacts” (Simberloff et al. 2005), not only in species
restoration but also in the introduction of alien species, deliberate
or not.

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We thank Lis Alban for her introduction to the topic of wild boar reintroduction in Denmark, and Mette Marie Andersen for her support with the Danish pig farm database. We are also thankful and want to acknowledge the fruitful discussions about the model construction we had with Jürgen Teuffert, Christoph Staubach, Matthias Greiner, Anders Stockmeyer, and Tommy Asferg. Comments from Jane U. Jepsen and two anonymous referees helped to improve previous versions of the manuscript. NF was supported by a Marie Curie Host Fellowship provided by the European Commission (HPMD-CT-2001-00109).

de Vos, C. J., H. W. Saatkamp, and A. A. Dijkhuizen. 2003.
The risk of the introduction of classical swine fever at regional level
in the European Union: a conceptual framework. Revue Scientifique
et technique de l'Office International des epizooties22:795-810.

Guberti, V., D. Rutili, G. Ferrari, C. Patta and A. Oggaino.
1998. Estimate the threshold abundance for the persistence of the
classical swine fever in the wild boar population of the eastern
Sardinia. Report on measures to control classical swine fever in
European wild boar. Document VI/7196/98-AL. Commission of the
European Communities, Directorate General VI for Agriculture, Perugia,
Italy.

Stauback, C., J. Teuffert, and H. H. Thulke. 1997. Risk
analysis and local spread mechanisms of classical swine fever. Pages
31-32 in Proceedings of the
Eigth Symposium of the International Society for Veterinary
Epidemiology and Economics (Paris, 1997). International Society for Veterinary Epidemiology and Economics, s.l.